標題: Titlebook: Data Engineering and Intelligent Computing; Proceedings of 5th I Vikrant Bhateja,Lai Khin Wee,T. M. Rajesh Conference proceedings 2022 The [打印本頁] 作者: 監(jiān)督 時間: 2025-3-21 19:06
書目名稱Data Engineering and Intelligent Computing影響因子(影響力)
書目名稱Data Engineering and Intelligent Computing影響因子(影響力)學(xué)科排名
書目名稱Data Engineering and Intelligent Computing網(wǎng)絡(luò)公開度
書目名稱Data Engineering and Intelligent Computing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Engineering and Intelligent Computing被引頻次
書目名稱Data Engineering and Intelligent Computing被引頻次學(xué)科排名
書目名稱Data Engineering and Intelligent Computing年度引用
書目名稱Data Engineering and Intelligent Computing年度引用學(xué)科排名
書目名稱Data Engineering and Intelligent Computing讀者反饋
書目名稱Data Engineering and Intelligent Computing讀者反饋學(xué)科排名
作者: surrogate 時間: 2025-3-21 20:58 作者: Forehead-Lift 時間: 2025-3-22 03:12
Application-Oriented Content Quality Analysis of Data Using Python,sary to find out the potential consumers or clients so that marketing will be done in an effective manner with addition to that the business makers can gain loyalty of consumers which will be beneficial for them in various perspectives. So, the quality of data is extremely important for business mak作者: Incumbent 時間: 2025-3-22 06:33
An Improved Similarity Measure Based on Collaborative Filtering for Sparsity Problem in Recommenderlts for the people. Recommender systems (RSs) play a significant role in generating accurate recommendations. Among the different types of RS, collaborative filtering-based (CF) RS is the most used due to its ability to produce recommendations that can fit the user’s varying preferences over time. C作者: 委托 時間: 2025-3-22 12:05
Detection and Classification of Bird Pest Using Spectrogram, Physical Imagery, and Convolutional Nesing physical and acoustic spectrogram imagery and optimized convolutional neural network classifiers. Two CNN models are designed to automatically and hierarchically learn spatially image features using 5 convolution layers of different filters followed by max polling 3 and fully connected 10 NN la作者: 成份 時間: 2025-3-22 12:59
Scatter Index: An Alternative Measure of Dispersion Based on Relative Frequency of Occurrence of ObCV) is a widely used as a standardized measure of dispersion. However, CV is not advisable in applications where mean of dataset is close to zero. In this paper, we have derived an alternate measure of dispersion called . which is based on relative frequency of observations. The novelty of the study作者: 成份 時間: 2025-3-22 19:47
Heart Failure Survival Prediction using Various Machine Learning Approaches, 32% of those deaths occurring globally. Heart attack and stroke accounted for 85% of these deaths. We used chi2 distributor, quantile transformer, polynomial feature, and XGboosting as machine learning approaches in this paper. In addition, the suggested model is used in a variety of machine learni作者: Synthesize 時間: 2025-3-22 21:48 作者: 滑動 時間: 2025-3-23 04:55 作者: Ebct207 時間: 2025-3-23 08:20 作者: endarterectomy 時間: 2025-3-23 11:32 作者: 泥土謙卑 時間: 2025-3-23 15:39
Segmentation of Epiphytes in Grayscale Images Using a CNN-Transformer Hybrid Architecture,Manually identifying epiphytes in these images is both time-consuming and prone to errors. Convolutional neural networks (CNNs) are the building blocks for almost all state-of-the-art image classification, detection, and segmentation tasks. The CNN algorithm generates good output results by using sp作者: mydriatic 時間: 2025-3-23 20:09 作者: certain 時間: 2025-3-23 22:37
Abstraction of Activity Diagram from Sequence Diagram,ows to implement the software systems using an object-oriented paradigm. The pictorial graphical representation of a software system is provided to the developer as well as to the end-user. The UML diagrams are broadly classified into two types with static and dynamic diagrams. The UML sequence and 作者: tenuous 時間: 2025-3-24 04:02 作者: phase-2-enzyme 時間: 2025-3-24 07:07
Topological Machine Learning Data Analysis for the Extraction of Robust Geometric Information, Several hierarchical data sets with high-dimensional data are the focus of this research. If a data set has complex samples, we assume that every sample has an irregular structure that can be represented in the form of an unordered graph. Topological data analysis (TDA) and geometric manifold learn作者: defenses 時間: 2025-3-24 11:53 作者: 細胞 時間: 2025-3-24 18:08 作者: 悅耳 時間: 2025-3-24 22:38 作者: 一起平行 時間: 2025-3-25 02:45
Michael H. Bonnet Ph.D.,Donna L. Arandl the images of okra fruit were captured using the same setup. Digital image processing and analysis technologies have been applied to derive the specified morphological and color-based DUS characteristics. The proposed methodology is objectively providing the DUS characteristics with fewer human in作者: 大廳 時間: 2025-3-25 07:11
Physiological Basis of Insomniaures. This project proposes a hybrid similarity measure more precisely a linear combination of similarity measures that utilize the advantage of each measure as well as by taking user rating preferences into consideration, hence able to achieve the least RMSE, MAE score for the datasets taken. The d作者: 有機體 時間: 2025-3-25 09:53 作者: 思想靈活 時間: 2025-3-25 15:17
Ruth Q. Wolever,Jennifer L. Bests machine learning models for analyzing, predicting, and classifying the breast cancer cells into benign and malignant cells. The paper compares the performance of these models with respect to their accuracy.作者: epidermis 時間: 2025-3-25 17:32
https://doi.org/10.1007/978-3-319-17139-5in memorizing long sequences. In this study, we have used TransU-Net, an architecture that combines the merits of both transformer and CNN for the segmenting images of ., an epiphyte, acquired with drones. The segmentation outputs generated from the trained models were evaluated with Dice score and 作者: Contend 時間: 2025-3-25 22:16
Heather K. Hood MA,Martin M. Antony PhDobject’s interactions, alternative ALT, and iterative LOOP and converts them into its amenable Activity-Table. Further, the automated tool scans the Activity-Table and then generates an equivalent activity diagram.作者: gregarious 時間: 2025-3-26 02:42 作者: 才能 時間: 2025-3-26 07:25
Derivation of DUS-Defined Physiological and Color Features of Okra Fruit Using Machine Vision Technl the images of okra fruit were captured using the same setup. Digital image processing and analysis technologies have been applied to derive the specified morphological and color-based DUS characteristics. The proposed methodology is objectively providing the DUS characteristics with fewer human in作者: 內(nèi)行 時間: 2025-3-26 10:48 作者: lattice 時間: 2025-3-26 14:20 作者: Evacuate 時間: 2025-3-26 18:35
Analysis and Prediction of Breast Cancer using Multi-model Classification Approach,s machine learning models for analyzing, predicting, and classifying the breast cancer cells into benign and malignant cells. The paper compares the performance of these models with respect to their accuracy.作者: colostrum 時間: 2025-3-26 22:54
Segmentation of Epiphytes in Grayscale Images Using a CNN-Transformer Hybrid Architecture,in memorizing long sequences. In this study, we have used TransU-Net, an architecture that combines the merits of both transformer and CNN for the segmenting images of ., an epiphyte, acquired with drones. The segmentation outputs generated from the trained models were evaluated with Dice score and 作者: FECK 時間: 2025-3-27 02:31 作者: 一窩小鳥 時間: 2025-3-27 07:15
Topological Machine Learning Data Analysis for the Extraction of Robust Geometric Information,with huge data sets, TDA is often utilised to extract structural and qualitative information. A set of hyper-spectral photos and simulated data show how well this approach works and how widely applicable it is. Here, we show that the hierarchical structure of hyper-spectral images is optimum. Our ne作者: nerve-sparing 時間: 2025-3-27 09:48
2367-3370 environment and industry. Further, the book also addresses the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.978-981-19-1558-1978-981-19-1559-8Series ISSN 2367-3370 Series E-ISSN 2367-3389 作者: 窒息 時間: 2025-3-27 16:04 作者: REIGN 時間: 2025-3-27 20:30 作者: Resection 時間: 2025-3-27 23:55 作者: dysphagia 時間: 2025-3-28 02:27
Insomnia in Comorbid Neurological Problemssary to find out the potential consumers or clients so that marketing will be done in an effective manner with addition to that the business makers can gain loyalty of consumers which will be beneficial for them in various perspectives. So, the quality of data is extremely important for business mak作者: pulmonary-edema 時間: 2025-3-28 06:53
Physiological Basis of Insomnialts for the people. Recommender systems (RSs) play a significant role in generating accurate recommendations. Among the different types of RS, collaborative filtering-based (CF) RS is the most used due to its ability to produce recommendations that can fit the user’s varying preferences over time. C作者: Facilities 時間: 2025-3-28 10:57
Insomnia in Children and Adolescentssing physical and acoustic spectrogram imagery and optimized convolutional neural network classifiers. Two CNN models are designed to automatically and hierarchically learn spatially image features using 5 convolution layers of different filters followed by max polling 3 and fully connected 10 NN la作者: 帶來 時間: 2025-3-28 17:23
Differential Diagnosis of InsomniaCV) is a widely used as a standardized measure of dispersion. However, CV is not advisable in applications where mean of dataset is close to zero. In this paper, we have derived an alternate measure of dispersion called . which is based on relative frequency of observations. The novelty of the study作者: Pathogen 時間: 2025-3-28 20:45
Michael H. Bonnet,Donna L. Arand 32% of those deaths occurring globally. Heart attack and stroke accounted for 85% of these deaths. We used chi2 distributor, quantile transformer, polynomial feature, and XGboosting as machine learning approaches in this paper. In addition, the suggested model is used in a variety of machine learni作者: freight 時間: 2025-3-28 23:55
Jeffrey Greeson,Jeffrey Brantleyis very important as it improves the treatment options and also improves the survival chance of patients. Mammography is identified as an ideal tool for breast cancer screening and is very effective and reliable. However, manually identifying abnormalities in breast and classifying them using mammog作者: Limerick 時間: 2025-3-29 05:42 作者: Notorious 時間: 2025-3-29 10:20
https://doi.org/10.1007/978-0-387-09593-6 required. Processing and selecting valuable data from these images take time. To overcome this difficulty, deep convolutional neural network algorithms can be assigned for processing huge image data. Deep convolutional neural networks (DCNNs) seem to provide substantial improvements in training eff作者: 釘牢 時間: 2025-3-29 14:59 作者: 難聽的聲音 時間: 2025-3-29 15:49
https://doi.org/10.1007/978-3-319-17139-5Manually identifying epiphytes in these images is both time-consuming and prone to errors. Convolutional neural networks (CNNs) are the building blocks for almost all state-of-the-art image classification, detection, and segmentation tasks. The CNN algorithm generates good output results by using sp作者: dialect 時間: 2025-3-29 20:04 作者: 清澈 時間: 2025-3-30 01:38
Heather K. Hood MA,Martin M. Antony PhDows to implement the software systems using an object-oriented paradigm. The pictorial graphical representation of a software system is provided to the developer as well as to the end-user. The UML diagrams are broadly classified into two types with static and dynamic diagrams. The UML sequence and 作者: CEDE 時間: 2025-3-30 05:42 作者: 原始 時間: 2025-3-30 08:40
Organic Gastrointestinal Disorders Several hierarchical data sets with high-dimensional data are the focus of this research. If a data set has complex samples, we assume that every sample has an irregular structure that can be represented in the form of an unordered graph. Topological data analysis (TDA) and geometric manifold learn作者: 小淡水魚 時間: 2025-3-30 15:03
J. Martin Maldonado-Duran,Clara Aisensteinase are merged to build a scene graph, which arranges the elements in a structured manner. Scene graphs have shown their proficiency in various tasks like image retrieval, visual question answering, and image generation. However, data is an essential aspect for such tasks, especially when the models作者: arthroscopy 時間: 2025-3-30 18:52 作者: NIP 時間: 2025-3-30 23:08
Prakash Chandra,Dana Billups-Bradleyred data and then again permits taking care of with fragmented data, ambiguity, vulnerability, and fluffiness. Along these lines, to remove significant and valuable examples from the text, some pre-preparing techniques and calculations are required. In this way, as a rule, text mining is the most co作者: 業(yè)余愛好者 時間: 2025-3-31 04:02 作者: 鍵琴 時間: 2025-3-31 05:51 作者: arthroplasty 時間: 2025-3-31 10:51
https://doi.org/10.1007/978-981-19-1559-8Artificial Intelligence; Data Engineering; Intelligent Computing; Cloud Computing; Machine Learning; Sign作者: NEXUS 時間: 2025-3-31 17:20 作者: BRIBE 時間: 2025-3-31 19:43
Conference proceedings 2022munication (ICICC 2021) organized by the Department of Computer Science and Engineering and the Department of Computer Science and Technology, Dayananda Sagar University, Bengaluru, India, on 26–27 November 2021. The book is organized in two volumes and discusses advanced and multi-disciplinary rese作者: 建筑師 時間: 2025-3-31 23:06 作者: 撤退 時間: 2025-4-1 03:10
Novel Approach to Abstract UML Use Case Diagram from Input Java Program,a program are taken as an input for the abstraction of the actors, use cases, and various relationships such as includes, extends, and generalization. The scope of the research work is restricted to object-oriented programming, hence Java programming language.作者: 不在灌木叢中 時間: 2025-4-1 08:42
Conference proceedings 2022that can be applied to provide practical solutions to a number of problems in society, the environment and industry. Further, the book also addresses the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.作者: 摸索 時間: 2025-4-1 10:59 作者: 范例 時間: 2025-4-1 17:53
Jeffrey Greeson,Jeffrey Brantleyemployed convolutional neural network (CNN) to classify the breast cancer cells into benign and malignant. Digital database for screening mammography (DDSM) dataset is used for training the CNN classifier. The CNN has achieved promising results by giving better performance and higher accuracy.
